The invention generally relates to automated programmable motion control systems, e.g., robotic, sortation and other processing systems, and relates in particular to programmable motion control systems intended for use in environments requiring that a variety of objects (e.g., articles, packages, consumer products etc.) be processed and moved to a number of processing destinations.
Many object distribution systems, for example, receive objects in a disorganized stream or bulk transfer that may be provided as individual objects or objects aggregated in groups such as in bags, arriving on any of several different conveyances, commonly a conveyor, a truck, a pallet a Gaylord, or a bin etc. Each object must then be distributed to the correct destination location (e.g., a container) as determined by identification information associated with the object, which is commonly determined by a label printed on the object. The destination location may take many forms, such as a bag, a shelf, a container, or a bin.
The processing (e.g., sortation or distribution) of such objects has traditionally been done, at least in part, by human workers that scan the objects, for example with a hand-held barcode scanner, and then place the objects at assigned locations. Many order fulfillment operations, for example, achieve high efficiency by employing a process called wave picking. In wave picking, orders are picked from warehouse shelves and placed at locations (e.g., into bins) containing multiple orders that are sorted downstream. At the sorting stage, individual articles are identified, and multi-article orders are consolidated, for example, into a single bin or shelf location, so that they may be packed and then shipped to customers. The process of sorting these articles has traditionally been done by hand. A human sorter picks an article, and then places the article in the so-determined bin or shelf location where all articles for that order or manifest have been defined to belong. Automated systems for order fulfillment have also been proposed. See, for example, U.S. Patent Application Publication No. 2014/0244026, which discloses the use of a robotic arm together with an arcuate structure that is movable to within reach of the robotic arm.
The identification of objects by code scanning generally either require manual processing, or require that the code location be controlled or constrained so that a fixed or robot-held code scanner (e.g., a barcode scanner) can reliably detect the code. Manually operated barcode scanners are therefore generally either fixed or handheld systems. With fixed systems, such as those at point-of-sale systems, the operator holds the article and places it in front of the scanner, which scans continuously, and decodes any barcodes that it can detect. If the article's code is not immediately detected, the person holding the article typically needs to vary the position or orientation of the article with respect to the fixed scanner, so as to render the barcode more visible to the scanner. For handheld systems, the person operating the scanner may look at the barcode on the article, and then hold the article such that the barcode is within the viewing range of the scanner, and then press a button on the handheld scanner to initiate a scan of the barcode.
Further, many distribution center sorting systems generally assume an inflexible sequence of operation whereby a disorganized stream of input objects is provided (by a human) as a singulated stream of objects that are oriented with respect to a scanner that identifies the objects. An induction element or elements (e.g., a conveyor, a tilt tray, or manually movable bins) transport the objects to desired destination locations or further processing stations, which may be a bin, a chute, a bag or a conveyor etc.
In conventional object sortation or distribution systems, human workers or automated systems typically retrieve object sin an arrival order, and sort each object or object into a collection bin based on a set of given heuristics. For example, all objects of a like type might be directed to a particular collection bin, or all objects in a single customer order, or all objects destined for the same shipping destination, etc. may be directed to a common destination location. Generally, the human workers, with the possible limited assistance of automated systems, are required to receive objects and to move each to their assigned collection bin. If the number of different types of input (received) objects is large, then a large number of collection bins is required.
FIG. 1 for example, shows an object distribution system 10 in which objects arrive, e.g., in trucks, as shown at 12, are separated and stored in packages that each include a specific combination of objects as shown at 14, and the packages are then shipped as shown at 16 to different retail stores, providing that each retail store receives a specific combination of objects in each package. Each package received at a retail store from transport 16, is broken apart at the store and such packages are generally referred to as break-packs. In particular, incoming trucks 12 contain vendor cases 18 of homogenous sets of objects. Each vendor case, for example, may be provided by a manufacturer of each of the objects. The objects from the vendor cases 18 are moved into decanted bins 20, and are then brought to a processing area 14 that includes break-pack store packages 22. At the processing area 14, the break-pack store packages 22 are filled by human workers that select items from the decanted vendor bins to fill the break-pack store packages according to a manifest. For example, a first set of the break-pack store packages may go to a first store (as shown at 24), and a second set of break-pack store packages may go to a second store (as shown at 26). In this way, the system may accept large volumes of product from a manufacturer, and then re-package the objects into break-packs to be provided to retail stores at which a wide variety of objects are to be provided in a specific controlled distribution fashion.
Such a system however, has inherent inefficiencies as well as inflexibilities since the desired goal is to match incoming objects to assigned collection bins. Such systems may require a large number of collection bins (and therefore a large amount of physical space, large investment costs, and large operating costs), in part, because sorting all objects to all destinations at once is not always most efficient. Additionally, such break-pack systems must also monitor the volume of each like object in a bin, requiring that a human worker continuously count the items in a bin.
Further, current state-of-the-art sortation systems also rely in human labor to some extent. Most solutions rely on a worker that is performing sortation, by scanning each object from an induction area (chute, table, etc.) and placing each object at a staging location, conveyor, or collection bin. When a bin is full, another worker empties the bin into a bag, box, or other container, and sends that container on to the next processing step. Such a system has limits on throughput (i.e., how fast can human workers sort to or empty bins in this fashion) and on number of diverts (i.e., for a given bin size, only so many bins may be arranged to be within efficient reach of human workers).
Unfortunately, these systems do not address the limitations of the total number of system bins. The system is simply diverting an equal share of the total objects to each parallel manual cell. Thus, each parallel sortation cell must have all the same collection bin designations; otherwise, an object may be delivered to a cell that does not have a bin to which the object is mapped. There remains a need, therefore, for a more efficient and more cost effective object processing system that processes objects of a variety of sizes and weights into appropriate collection bins or trays of fixed sizes, yet is efficient in handling objects of varying sizes and weights.